Digital watermarks for checking authenticity of printed objects

ABSTRACT

The invention provides methods for embedding digital watermarks for authentication of printed objects, and corresponding methods for authenticating these objects. One aspect of the invention is a method of embedding a digital watermark in a digital image to be printed on an object. The method embeds an auxiliary signal in the digital image so that the auxiliary signal is substantially imperceptible, yet machine readable. It converts the image to a halftone image using a halftoning process. If copies are made of the printed image, the image characteristics change due a change in the halftoning process used to create the copies. These changes are detected to determine whether a suspect document is authentic.

RELATED APPLICATION DATA

This application is a continuation of U.S. patent application Ser. No.09/938,870, filed Aug. 23, 2001 (now U.S. Pat. No. 7,246,239).

The subject matter of the present application is related to thatdisclosed in U.S. patent application Ser. No. 09/840,016, filed Apr. 20,2001 (Now U.S. Pat. No. 6,760,464), 60/263,987, filed Jan. 24, 2001,Ser. No. 09/689,226, filed Oct. 11, 2000, and Ser. No. 09/234,780, filedJan. 20, 1999, which are hereby incorporated by reference.

TECHNICAL FIELD

The invention relates to steganography and data hiding, and specificallyrelates to the use of digital watermarks for authentication of printedobjects.

BACKGROUND AND SUMMARY

Digital watermarking is a process for modifying physical or electronicmedia to embed a machine-readable code into the media. The media may bemodified such that the embedded code is imperceptible or nearlyimperceptible to the user, yet may be detected through an automateddetection process. Most commonly, digital watermarking is applied tomedia signals such as images, audio signals, and video signals. However,it may also be applied to other types of media objects, including textdocuments (e.g., through line, word or character shifting), software,multi-dimensional graphics models, and surface textures of objects.

Digital watermarking systems typically have two primary components: anencoder that embeds the watermark in a host media signal, and a decoderthat detects and automatically reads the embedded watermark from asignal suspected of containing a watermark (a suspect signal). Theencoder embeds a watermark by altering the host media signal. Thereading component analyzes a suspect signal to detect whether awatermark is present. In applications where the watermark encodesinformation, the reader extracts this information from the detectedwatermark.

Several particular watermarking techniques have been developed. Thereader is presumed to be familiar with the literature in this field.Particular techniques for embedding and detecting imperceptiblewatermarks in media signals are detailed in the assignee's applicationSer. No. 09/503,881 (Now U.S. Pat. No. 6,614,914) and U.S. Pat. No.6,122,403, which are hereby incorporated by reference.

This document describes methods for embedding digital watermarks forauthentication of printed objects, and corresponding methods forauthenticating these objects. One such method embeds an auxiliary signalin the digital image so that the auxiliary signal is substantiallyimperceptible, yet machine readable. It converts the image to a halftoneimage using an inherently unstable halftone screen structure that islikely to cause ink flow errors when reproduced. The errors introducedby reproducing the unstable halftone screen structure incorrectly areautomatically detectable by reading the auxiliary signal.

An authentication method receives a digital image scanned of the printedobject, and detects a digital watermark in the digital image. It thenuses a measurement of strength of the digital watermark to detectreproduction errors due to inaccurate reproduction of unstable halftonescreen structures in the printed object. Another method ofauthenticating a printed object uses different watermarks in the object.This method detects a first digital watermark from a substrate of theprinted object, and detects a second digital watermark from an imagescanned from the printed object. It uses the relationship between thefirst and second digital watermarks to determine authenticity of theprinted object.

Another method detects a visible fiducial in an image scanned from theprinted object, and detects a location of a digital watermark hidden inthe printed object. It determines authenticity of the printed object bycomparing the location of the digital watermark to the visible fiducial.

One aspect of the invention is a method of embedding a digital watermarkin a digital image to be printed on an object. This method generates animage to be printed based on the digital image, including converting thedigital image to a halftone image, and embedding an auxiliary signal inthe digital image so that the auxiliary signal is substantiallyimperceptible, yet machine readable. The method encodes a message in theauxiliary signal that includes halftone information, which isautomatically readable from a printed version of the image to enablechecking whether measured attributes of the printed version of the imagecorrespond to the halftone information.

Another aspect of the invention is a method of authenticating a printedobject comprising. This method receives a digital image scanned of theprinted object, detects a digital watermark in the digital image,extracts halftone information from the digital watermark, and evaluatesthe digital image for attributes that correspond to the halftoneinformation from the digital watermark to determine authenticity of theprinted object.

Further features will become apparent with reference to the followingdetailed description and accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a flow diagram of watermark embedding and halftonescreening process using inherently unstable screens to create anauthentication watermark on a printed object.

FIG. 2 illustrates an example showing different halftone structures,including a relatively stable structure (A), and inherently unstablestructures (B and C).

FIG. 3 is a diagram illustrating a process for detecting anauthentication watermark from a scanned image of the watermarked object,and for assessing the validity of the watermark signal.

DETAILED DESCRIPTION

Using Inherently Unstable Structure as Screening Elements

FIG. 1 illustrates a flow diagram of watermark embedding and halftonescreening process using inherently unstable screens to create anauthentication watermark on a printed object. This process generates adigital watermark signal and embeds it in a halftone image. The screensused to create the halftone image have inherently unstable dotstructures that are difficult to reproduce. As such, if the printedobject is copied (e.g., scanned and re-printed) the dot structures arelikely to change. A watermark reader processes a digital image of theobject, and detects errors in the watermark signal due to the changes inthe ink structures. The extent of these errors indicate the extent towhich the printed object is likely to be a counterfeit.

Turning to FIG. 1, this example digital watermark embedding processstarts with a message (100) to be hidden in the printed document. Themessage comprises a set of binary (or M-ary) symbols, including bothfixed symbols to assist in detection and message interpretation (e.g., amessage common to a particular message protocol), and variable symbolsto carry a variable message (e.g., a unique message for a particularprinted item). The message is error correction encoded (e.g.,convolution, turbo, BCH, repetition coding)(102), and then spreadspectrum modulated with a carrier signal (104). In this example, thecarrier signal comprises a pseudorandom image signal that corresponds toa block of image samples in the host image. The spread spectrummodulation function may be implemented using a variety of spreadingfunctions, such as convolving, multiplication, XOR, XNOR operationsbetween the message signal and the carrier to create a watermark signal.Preferably, the watermark signal has a calibration signal component,e.g., signal patterns such as peaks in the autocorrelation or Fourierdomain that facilitate detection, and calculation of rotation, scale andtranslation parameters of the watermark signal in an image scan of aprinted object carrying the watermark. Examples of spread spectrummodulation and calibration signals are disclosed in co-pendingapplication Ser. No. 09/503,881 and U.S. Pat. No. 6,122,403,incorporated above.

In this implementation, a digital watermark signal is generated at asource resolution that is lower than the target resolution of the halftone dots used to create the printed image. The watermark signal isembedded using an embedding process (106) that adds samples of thewatermark signal to corresponding samples of the host image (108). Theembedding function may also include perceptual masking of the watermarksignal, such as adjusting the watermark signal strength according toHuman Visibility System modeling filters that determine the capacity ofthe host image to hide the watermark signal. The embedding process (106)creates a watermarked image signal comprising an array of multi-levelper pixel values at specified resolution.

Next, the watermarked image signal is converted to an image comprised ofhalftone dots at a target resolution that is higher than the sourceresolution of the watermarked signal (110). The half tone dot representsthe presence or absence of ink at a particular spatial location on aprinted object. The halftone process uses inherently unstable screens(112) to convert selected multi-level per pixel samples in thewatermarked image to corresponding halftone dot structures comprising anarray of halftone dots.

In some applications, like corporate logos, graphic symbols, etc. thehost image can be particularly adapted to carry a watermark signal. Inother words, the watermark signal and corresponding image are designedtogether to form the watermarked image. In this case, there is no needfor a generic watermark embedding technique that is broadly applicableto a variety of images. Also, this enables the image to be designed withspecial features that assist in watermark detection, like visiblefiducials that enable the watermark reader to align the imagegeometrically before detecting the watermark or performing other imageanalysis. Conventional pattern recognition and registration routines maybe used to align the image as a pre-process step before authentication.

FIG. 2 illustrates an example showing different halftone structures,including a relatively stable structure (A), and inherently unstablestructures (B and C). To create an authentic printed object, theseunstable structures are used to create a halftone image, which is thenprinted with a high quality printer (110) capable of accuratelyretaining the unstable structure of ink on the printed object. Later, ifthe printed object is scanned and printed, it is difficult to reproducethe structures on typical ink jet printers, even if the authentic objectis scanned with a high resolution scanner. For such ink jet printers, aninherently unstable structure creates the likelihood of ink flow suchthat ink jet printer is unlikely to reproduce the structure with thesame ink coverage (e.g. the ink density over the same area changescausing a change in color or luminance of the pixel). The ink flow atthe boundary of the unstable structure causes more area to be covered,and as such, an ink jet printer with such ink flow cannot accuratelyreproduce the unstable structure without changing the density of inkover the area covered by the structure in the authentic printed object.

As an example, consider the case where the watermarked signal has aresolution of 100 dpi and the halftone dot resolution is 500 dpi. Inother words, each 100 dpi pixel in the watermarked signal corresponds toa 5 by 5 array of halftone dots. To represent a multilevel per pixelvalue of 8/25, any of the structures A-C could be used, but structures Band C are more likely to cause ink flow problems if a counterfeitertries to reproduce them using an ink jet printer with ink flow problems.For example, the same 5 by 5 area may be reproduced as 10/25 (10halftone dots with ink) instead of 8/25 (8 halftone dots with ink).

Traditional halftone screening algorithms avoid square clusters ofhalftone dots in cases where about 50% of the dots are turned on. Thereason for avoiding this pattern of halftone dot clusters is that itcauses ink to flow between the dots where the corners of the squareclusters meet. Structure D in FIG. 2 illustrates an example of anunstable screen with square clusters joined at the corners. Whileavoided in the traditional case, this arrangement may be usedadvantageously to authenticate a printed object because certain printingpresses can represent the pattern accurately on paper. However, whenreproduced by the counterfeiter on a different printer, error due to inkflow are likely.

The error in reproduction can cause the watermark to be un-detectable byan automated reader, or may create enough errors in the watermark signalto indicate that the printed object is likely a fake. In the first case,if the watermark reader cannot detect the watermark, the printed objectis deemed not to be authentic. In the second case, the authenticity isdetermined by evaluating the watermark strength relative to a threshold.This process embeds a watermark at a sufficiently low resolution andsufficiently high strength to enable the watermark to be read usingcommercial scanners and web cameras, and it also enables detection ofinvalid printed objects.

FIG. 3 is a diagram illustrating a process for detecting anauthentication watermark from a scanned image of the digitallywatermarked object, and for assessing the validity of the watermarksignal. First, the user holds the printed object up to a web camera orplaces it on an image scanner plate. The watermark reader receives adigital image (120) of the printed object, and pre-processes it toprepare for watermark detection (122).

The pre-processing (122) entails a conversion to the color plane inwhich the watermark signal is embedded (e.g., blue channel, yellowchannel, luminance, chrominance, etc.), and a filtering of blocks of theimage to identify candidate blocks that are likely to have theauthentication watermark. Examples of the filtering include looking forportions of the image with a certain signal activity (texture), color,edge concentration, etc.

Next, the watermark detector proceeds to detect the watermark signal anddetermine orientation parameters of watermark signal blocks (e.g.,rotation, scale, translation). The candidate image blocks identified inthe pre-processing stage are transformed into a transform domain fordetection of the calibration component. For example, candidate blocksare transformed into an autocorrelation domain or Fourier domain, wherepeaks of the calibration component are detected and correlated with areference signal having attributes of the known calibration signalcomponent. An example of this technique using the Fourier-Mellintransform to recover rotation and scale is described in application Ser.No. 09/503,881 (Now U.S. Pat. No. 6,614,914) and U.S. Pat. No.6,122,403, incorporated above. This example detector correlates thepseudorandom phase information of the calibration signal with phaseinformation of the received image, after compensating for rotation andscale to get the coordinates of the origin of a watermark block.

Next, the watermark detector reads the message embedded in the watermarksignal (128). In this implementation, the detector is calibrated to readthe watermark at its original resolution at the time of embedding (e.g.,100 dpi in the example above). To reduce the interference of theoriginal host signal, the detector predicts the original signal andsubtracts it, leaving an estimate of the watermark signal. The detectorthen performs the inverse of the spread spectrum modulation to computeraw estimates of the error correction encoded message symbols. These aresoft estimates weighted by a probability reflecting the statisticalconfidence in the accuracy of the symbol. The soft estimates aresupplied to an error correction decoder compatible with the one in theencoder, which generates a message, including the fixed and variablemessage symbols.

Error detection symbols, such as CRC bits computed on the message,indicate whether the decoded message is valid. If the detector is unableto extract a valid watermark, the printed object is deemed to be a copy.A successful watermark detection is measured by the degree ofcorrelation between the detected signal and the reference signal in thecalibration phase, and/or a valid message as determined by the errordetection evaluation.

If a valid watermark message is recovered, the detector proceeds tomeasure the strength of the watermark signal. There are multiple metricsfor assessing watermark strength, including the degree of correlationbetween the reference signal and the detected signal, and a measure ofsymbol errors in the raw message estimates. One way to measure thesymbol errors is to reconstruct the raw message sequence using the sameerror correction coding process of the embedder on the valid messageextracted from the watermark. This process yields, for example, a stringof 1000 binary symbols, which can be compared with the binary symbolsestimated at the output of the spread spectrum demodulator. The strongerthe agreement between the reconstructed and detected message, thestronger the watermark signal.

More specifically, an approach for measuring the strength of thewatermark signal is as follows:

-   1. Use the message payload read from the watermark to re-create the    original embedded bit sequence (including redundantly encoded bits    from error correction coding) used for the watermark.-   2. Convert the original bit sequence so that a zero is represented    by −1 and a one is represented by 1.-   3. Multiply (element-wise) the soft-valued bit sequence used to    decode the watermark by the sequence of step 2.-   4. Create one or more measures of watermark strength from the    sequence resulting in the previous step. One such measure is the sum    of the squares of the values in the sequence. Another measure is the    square of the sum of the values in the sequence. Other measurements    are possible as well. For example, soft bits associated with high    frequency components of the watermark signal may be analyzed to get    a strength measure attributed to high frequency components. Such    high frequencies are likely to be more sensitive to degradation due    to photocopying, digital to analog and analog to digital conversion,    scanning and re-printing, etc.-   5. Compare the strength measures to thresholds to decide if the    suspect image has been captured from an original or a copy of the    printed object. The threshold is derived by evaluating the    difference in measured watermark strength of copied vs. original    printed objects on the subject printer platform used to create the    original, and a variety of copiers, scanners and printers used to    create copies.

This same technique of measuring symbol errors can be applied to two ormore different watermarks embedded at different spatial resolutions.Each of the watermarks may have the same or different message payloads.In the first case where the watermarks have the same message payloads,the message extracted from one of the watermarks may be used to measurebit errors in each of the other watermarks. For example, the messagepayload from a robust watermark embedded at a low spatial resolution maybe used to measure the bit errors from a less robust watermark at ahigher spatial resolution. If the watermarks carry different messagepayloads, then error detection bits, such as CRC bits, can be used ineach message payload to ensure that the message is accurately decodedbefore re-creating the original, embedded bit sequence.

Using two or more different watermarks enables a threshold to be setbased on the ratio of the signal strength of the watermarks relative toeach other. In particular, the signal strength of a first watermark at ahigh resolution (600-1200 dpi) is divided by the signal strength of asecond watermark at a lower resolution (75-100 dpi). In each case, thesignal strength is measured using a measure of symbol errors or someother measure (e.g., correlation measure).

If the measured strength exceeds a threshold, the detector deems thewatermark signal to be authentic and generates an authentication signal(132). This signal may be a simple binary value indicating whether ornot the object is authentic, or a more complex image signal indicatingwhere bit errors were detected in the scanned image.

The watermark and host signal can be particularly tailored to detectcopying by photo duplication and printing/re-scanning of the printedobject. This entails embedding the watermark with selected screeningstructures at particular spatial frequencies/resolutions that are likelyto generate message symbol errors when the object is re-printed. Thisdetection process has an additional advantages in that it enablesautomatic authentication, it can be used with lower quality cameradevices such as web cams and common image scanners, and it allows thewatermark to serve the functions of determining authenticity as well ascarrying a message payload useful for a variety of applications.

The message payload can include an identifier or index to a databasethat stores information about the object or a link to a network resource(e.g., a web page on the Internet). The payload may also include acovert trace identifier associated with a particular authentic item,batch of items, printer, or distributor. This enables a counterfeitobject, or authentic object that has been printed without authority tobe detected and traced to a particular source, such as its printer,distributor or batch number.

The payload may also carry printer characteristics or printer typeinformation that enables the watermark reader to adapt its detectionroutines to printer types that generated the authentic object. Forexample, the payload may carry an identifier that specifies the type ofhalftoning used to create the authentic image, and more specifically,the attributes of the halftone screen. With this information, the readercan check authenticity by determining whether features associated withthe halftone screen exist in the printed object. Similarly, the readercan check for halftone screen attributes that indicate that a differenthalftone screen process has been used (e.g., a counterfeit has beencreated using a different halftone screen). One specific example is apayload that identifies the halftone screen type and paper type. Thereader extracts this payload from a robust watermark payload and thenanalyzes the halftone screen and paper attributes to see if they matchthe halftone type and paper type indicated in the watermark payload. Forexample, the halftone type can specify the type of unstable screen usedto create an authentic image. If this unstable screen is not detected(e.g., by absence of a watermark embedded in the unstable screen), thenthe image is considered to be a fake.

A related approach for analyzing halftone type is to look for halftoneattributes, like tell-tale signs of stochastic halftone screens vs.ordered dither matrix type screens. Dither matrix screens used in lowend printers tend to generate tell tale patterns, such as a pattern ofpeaks in the Fourier domain that differentiate the halftone process froma stochastic screen, such as an error diffusion process, which does notgenerate such tell-tale peaks. If the reader finds peaks where none wereanticipated, then the image is deemed a fake. Likewise, if the readerfinds no peaks where peaks were anticipated, then the image is alsodeemed a fake. Before performing such analysis, it is preferable to usethe embedded digital watermark to re-align the image to its originalorientation at the time of printing. Attributes due to the halftonescreen can then be evaluated in a proper spatial frame of reference. Forexample, if the original ordered dither matrix printer created an arrayof peaks in the Fourier domain, then the peak locations can be checkedmore accurately after the image is realigned.

Additional Authentication Methods

Another way to authenticate the printed object is to embed separatedigital watermarks in the object, including one in the substrate of theobject, and another hidden in a visible image printed on the substrate.A verification device looks for these watermarks in a scanned image ofthe object, and used the expected relationship between them to checkauthenticity. In one case, the presence of one watermark without theother indicates that the object is a fake. For example, if the image onan authentic object is scanned and re-printed on another substrate of afake object, then the new substrate will not have the watermark embeddedin the substrate.

In one implementation, the substrate carries a digital watermark in theform of the calibration signal as described above. This digitalwatermark is embedded so as to be substantially imperceptible bymodulating the surface micro-topology of the substrate to form thecalibration signal, which is a pseudorandom pattern with registrationpeaks in a transform domain (e.g., autocorrelation or Fourier transformdomain). In the detection/verification process, a watermark detectorprocesses a scanned image of the object, looking for the calibrationsignal. If none is present, or only a weak signal as measured by theextent of correlation with the known calibration signal, then the objectis deemed a fake.

One form of substrate watermark is a layer of UV ink or lacquer thatmodulates the topology of the object surface to form the substratewatermark signal. This UV ink is transparent or semi-transparent, yetforms a surface topology that modulates the luminance of the objectsurface to embed the watermark signal. This layer of ink can be formedon the surface of the object by printing an image of the substratewatermark onto the object using the UV ink or lacquer.

The other watermark may be embedded in a luminance or other colorchannel of a color image or gray-scale image printed on the object. Forthe sake of explanation, let's refer to this other watermark as theimage watermark, as opposed to the substrate watermark.

For additional verification, the substrate and image watermarks cancarry payload information that must satisfy a predetermined relationshipto establish the authenticity of the object bearing these digitalwatermarks. For example, the message payloads may need to satisfy apredetermined relationship (e.g., one is a cryptographic transform ofthe other).

Either the substrate or the image watermark may also be embedded atpredetermined locations relative to the other watermark or some visiblefiducial on the object that can be detected automatically. Such ageometric relationship between the digital watermark and a fiducial, orbetween different digital watermarks is designed to be difficult tore-produce accurately in a copy of the object. To check authenticity,the watermark location is extracted and checked relative to the locationof a second watermark or fiducial. If the relative positions of thewatermark and fiducial/second watermark do not fall within apredetermined tolerance, the object is deemed to be a fake. The fiducialmay be a simple visible pattern detectable by pattern recognitiontechniques, the edge of page, the border of text (e.g., margin of thepage), or some other distinguishable structure.

CONCLUDING REMARKS

Having described and illustrated the principles of the technology withreference to specific implementations, it will be recognized that thetechnology can be implemented in many other, different, forms. Toprovide a comprehensive disclosure without unduly lengthening thespecification, applicants incorporate by reference the patents andpatent applications referenced above.

The methods, processes, and systems described above may be implementedin hardware, software or a combination of hardware and software. Forexample, the auxiliary data encoding processes may be implemented in aprogrammable computer or a special purpose digital circuit. Similarly,auxiliary data decoding may be implemented in software, firmware,hardware, or combinations of software, firmware and hardware. Themethods and processes described above may be implemented in programsexecuted from a system's memory (a computer readable medium, such as anelectronic, optical or magnetic storage device).

The particular combinations of elements and features in theabove-detailed embodiments are exemplary only; the interchanging andsubstitution of these teachings with other teachings in this and theincorporated-by-reference patents/applications are also contemplated.

1. A method of embedding a digital watermark in a digital image,comprising: generating an image adapted to be applied to an object basedon the digital image, including: converting the digital image to atleast one halftone image; and embedding an auxiliary signal in thedigital image so that the auxiliary signal is substantiallyimperceptible, yet machine readable; and encoding a message in theauxiliary signal that includes halftone information, wherein thehalftone information is configured to be automatically readable from aprinted version of the image to enable checking whether measuredattributes of the printed version of the image correspond to thehalftone information.
 2. The method of claim 1, further comprisingspread spectrum modulating a carrier signal with the message to form theauxiliary signal.
 3. The method of claim 2, wherein the messagecomprises information indicating the type of halftone conversion used tocreate the halftone image.
 4. The method of claim 1, wherein theauxiliary signal is embedded in the digital image prior to convertingthe digital image to a halftone image.
 5. A method of authenticating aprinted object, comprising: receiving a digital image scanned of theprinted object; detecting a digital watermark in the digital image;extracting halftone information from the digital watermark; andevaluating the digital image for attributes that correspond to thehalftone information from the digital watermark to determineauthenticity of the printed object.
 6. The method of claim 5, furthercomprising, before evaluating the digital image, aligning the digitalimage geometrically based on the digital watermark.
 7. The method ofclaim 5, wherein evaluating the digital image comprises evaluating thedigital image for attributes corresponding to a halftone screen typeidentified in the halftone information.
 8. The method of claim 5,wherein evaluating the digital image comprises evaluating the digitalimage for signal peaks corresponding to a halftone type identified inthe halftone information.
 9. A computer-readable storage device havinginstructions stored thereon that, if executed by a computing device,cause the computing device to perform operations comprising: generatingan image adapted to be applied to an object based on the digital image,including: converting the digital image to at least one halftone image;and embedding an auxiliary signal in the digital image so that theauxiliary signal is substantially imperceptible, yet machine readable;and encoding a message in the auxiliary signal that includes halftoneinformation, wherein the halftone information is configured to beautomatically readable from a printed version of the image to enablechecking whether measured attributes of the printed version of the imagecorrespond to the halftone information.
 10. A computer-readable storagedevice having instructions stored thereon that, if executed by acomputing device, cause the computing device to perform operationscomprising: receiving a digital image scanned of a printed object;detecting a digital watermark in the digital image; extracting halftoneinformation from the digital watermark; and evaluating the digital imagefor attributes that correspond to the halftone information from thedigital watermark to determine authenticity of the printed object. 11.An apparatus comprising: a processor configured to: generate an imageadapted to be applied to an object based on the digital image,including: converting the digital image to at least one halftone image;and embedding an auxiliary signal in the digital image so that theauxiliary signal is substantially imperceptible, yet machine readable;and encode a message in the auxiliary signal that includes halftoneinformation, wherein the halftone information is configured to beautomatically readable from a printed version of the image to enablechecking whether measured attributes of the printed version of the imagecorrespond to the halftone information.
 12. An apparatus comprising: aprocessor configured to: receive a digital image scanned of a printedobject; detect a digital watermark in the digital image; extracthalftone information from the digital watermark; and evaluate thedigital image for attributes that correspond to the halftone informationfrom the digital watermark to determine authenticity of the printedobject.